Database systems typically store database objects (e.g. tables, indexes, etc.) on disk, and load data items from those database objects into volatile memory on an as-needed basis. Once loaded into volatile memory, the data items may remain cached in volatile memory so that subsequent accesses to the same data items will not incur the overhead of accessing a disk. Those data items may be replaced in cache, for example, to make room in volatile memory to store other data items that have been requested.
Rather than load individual data items on a per-item basis, entire database objects, or portions thereof, may be pre-loaded into volatile memory. Various approaches for loading entire database objects, or selected portions thereof, into volatile memory to speed up database operation processing are described in U.S. patent application Ser. No. 14/377,179, entitled “Mirroring, In Memory, Data From Disk To Improve Database operation Performance”, filed Jul. 21, 2014, referred to herein as the “Mirroring” application, the contents of which is incorporated herein in its entirety.
According to the approaches described in the Mirroring application, database objects, or portions thereof, are stored in volatile memory in a different format than the format that those same objects have on disk. For example, the in-memory copies of the objects may be stored in a column-major format, while the on-disk copies are stored in a row-major format. An in-memory version or copy of an object (or selected portions thereof), is referred to herein as an In-Memory-Copy (IMC). The set of data that is copied from disk into volatile memory to create an IMC is referred to herein as a “chunk”.
When a node commits a transaction that changes data in a chunk, the change becomes permanent and must be visible to all nodes that use that data. Thus, when executing a subsequent transaction with a snapshot time after the commit time of the transaction that made the change, any remote node that accesses the IMC for that data should immediately use the changed data. This concept is referred to herein as coherency. Maintaining coherency across multiple nodes is difficult in a dual format database because data as stored on disk does not directly map to how data is stored in volatile memory.
The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.